All news in category “Vendor and Hyperscaler Watch”

🔒 AWS Config now supports internal service linked rules, allowing AWS services to evaluate resource configurations using AWS Config managed rules. These rules let AWS services like AWS Security Hub CSPM deploy and manage service-specific evaluations, with results sent directly to the deploying service. Evaluations occur at no charge from AWS Config and run independently of customer-managed recorders and rules, preserving existing inventory and compliance workflows. The feature is available in commercial, GovCloud, and China Regions.

🔒 At Microsoft Build 2026, Microsoft announced new security capabilities to integrate protection across the development lifecycle, addressing insecure code, agent proliferation, and model risk. The expanded preview of the multi-model agentic scanning harness (codename MDASH) integrates with Microsoft Defender to orchestrate hundreds of AI agents for exploit discovery. New tools such as Agent 365, MXC SDK, and Purview enhancements provide runtime controls, data protection, and governance to help developers and security teams act earlier and with consistent oversight.

🔧 AWS Deadline Cloud now supports persistent storage for Service-Managed Fleets (SMF), enabling data retention across worker lifecycle events. Previously, SMF workers used ephemeral storage and required reinstalling software and assets after recycling. Now Deadline Cloud attaches persistent Amazon EBS volumes to SMF workers to preserve Conda environments, Perforce workspaces, shader caches, and asset collections, reducing startup time. You can configure volume counts per worker and set TTLs to balance retention and cost; availability and pricing match existing SMF EBS offerings.

🚀 Google Cloud Storage (GCS) is positioned as the preferred home for large-scale unstructured data and as a foundational component for production AI agents. This post highlights customer examples—Palo Alto Networks and Snap—using GCS as agent memory and analytics storage, and explains how the Model Context Protocol (MCP) enables secure, standardized access. Google offers two MCP server options: a fully managed Remote MCP server for easy, scalable deployments, and a self-managed Local MCP server for custom tooling and transformations, both integrated with Google Cloud security, observability, and tooling.

🧭 Microsoft highlights how AI-driven agentic workflows demand a shared data context. Microsoft Fabric is presented as a unified data and AI platform that enables developers and agents to build production-ready apps by providing consistent organizational context. New announcements include the open-source Rayfin SDK/CLI for rapid backend deployment and Azure HorizonDB (PostgreSQL-compatible) in public preview, optimized for AI workloads.

🚀 Microsoft announced early access preview of Azure Cobalt 200 Arm-based VMs at Build 2026, delivering up to 50% generational performance improvements over Cobalt 100 for agentic AI and cloud-native Linux workloads. The Cobalt 200 SoC, built on Arm Neoverse V3 and TSMC 3nm, features chiplets, custom accelerators, and enhanced memory and security capabilities. New VM families (including high-memory and dense local storage) expand deployment choices and are available in selected preview regions.

🔧 Amazon SageMaker Studio's quick setup now completes in under twenty seconds, down from over two minutes, letting users rapidly move from sign-in to a fully configured Studio environment. Newly created Studio environments automatically receive serverless model customization permissions via a new managed policy, AmazonSageMakerModelCustomizationCoreAccess, enabling fine-tuning, evaluation, and deployment without manual IAM role configuration. Existing environments receive actionable guidance to add the permissions. The feature is available in all AWS Commercial Regions that support SageMaker Studio.

🔒 This post shows how SaaS providers can use Amazon Bedrock AgentCore resource-based policies to control multi-tenant access to a shared AgentCore Runtime and Runtime endpoint. It walks through two tenant scenarios: cross-account access for Example Corp and VPC-restricted access for AnyCompany, demonstrating how to apply resource-level Allow and explicit Deny conditions. The article covers required IAM permissions, example policy files, and verification steps to ensure network- and identity-based constraints are enforced.

🔍 At Google Cloud Next, Google announced the preview of graph algorithms in Spanner Graph, bringing Google Research’s graph mining capabilities natively to Spanner to deliver faster, cost-effective, large-scale structural analytics. The feature integrates with ISO GQL, runs on dedicated compute to avoid transactional impact, and scales to graphs with tens of billions of edges. Results can be written back to Spanner or exported to Cloud Storage.

🛠️ Microsoft Foundry presents a unified platform to select, evaluate, optimize, and operate AI models across the full application lifecycle. The post emphasizes that production systems require continuous model selection, validation on real data, cost and latency management, and governance rather than simply picking the most capable model. Foundry adds new model families and Fireworks AI for production-grade open model inference via a single Azure endpoint with enterprise SLAs. It provides model routing, benchmarking with custom datasets, continuous evaluation, and operational controls like versioning, observability, and rollout strategies.

🔎 Foundry IQ streamlines bringing enterprise and external knowledge into agent workflows by unifying content, improving ingestion, and offering a serverless model for retrieval. The service provides a Model Context Protocol (MCP) server, integrates Microsoft Web IQ for low-latency external context, and includes GA security and compliance features. Serverless Developer tier is in public preview with CU-based billing estimates and scale-to-zero capacity.

🚀 The post announces gcs-analytics-core, an open-source Java library that centralizes performance optimizations for Google Cloud Storage (GCS) across analytics engines like Apache Iceberg and Spark. Integrated natively in Apache Iceberg 1.11.0+, the library provides vectored I/O and smart Parquet footer prefetching to reduce I/O latency and improve throughput. Benchmarks using TPC-DS demonstrate sizable scan and execution time improvements across dataset sizes, and the project is available on GitHub for contributions and review.

🚀 Today AWS adds durability to Amazon ElastiCache, allowing workloads that need microsecond read latency but cannot tolerate data loss to run on ElastiCache. The feature stores data durably across multiple Availability Zones using a Multi‑AZ transactional log for fast failover, recovery, and node restarts. Two durability modes—synchronous and asynchronous writes—let you trade off zero data loss with millisecond write latency or microsecond write latency with potential brief data loss.

🛰️ Amazon Location Service introduced public transit and intermodal routing in the Routes API, adding two travel modes, Transit and Intermodal, to the CalculateRoutes operation. Developers can now compute journeys combining buses, trains, ferries, walking, driving, taxi, and rental segments, with stop details, departure/arrival times, and last-mile support. These features support mobility, logistics, commutes, and urban planning, and are available in multiple AWS Regions globally.

📣 AWS announced that AWS Cost and Usage Report 2.0 (CUR 2.0) now integrates directly with AWS Athena and AWS Redshift, enabling customers to query CUR data in Amazon S3 using standard SQL without custom warehousing. Exports are delivered in optimal formats (Parquet, GZIP) and include metadata, templates, table definitions, and loading instructions to accelerate setup. CUR 2.0 refreshes automatically update Athena and Redshift tables, and the feature is available in all commercial AWS Regions except GovCloud (US) and China Regions.

🔔 Amazon RDS for SQL Server now supports Bring Your Own Media (BYOM), enabling customers to migrate SQL Server workloads to a managed AWS service while reusing existing Microsoft SQL Server licenses and Software Assurance via Microsoft's License Mobility program. The capability integrates with AWS License Manager to help track license usage and maintain compliance. BYOM reduces the need to purchase additional SQL Server licenses or wait for existing agreements to expire when moving to RDS. It aims to simplify migrations from on‑premises, other clouds, or self‑managed EC2 deployments.

🔬 AWS HealthOmics now supports Nextflow version 26.04, enabling customers to use new Nextflow features like record types, the strict syntax parser, workflow output summaries, and agent logging mode. The service is HIPAA-eligible and provides fully managed bioinformatics workflows for healthcare and life sciences. Nextflow v26.04 is available across all AWS HealthOmics regions, improving pipeline reliability, readability, and integration with downstream tools.

🔬 AWS HealthOmics now lets customers specify the Nextflow engine version at run time via the StartRun API, enabling explicit version pinning for controlled migration. Supported versions include 22.04, 23.10, 24.10, 25.10, and 26.04 via a new engine-settings parameter. This run-time override takes precedence over manifest.nextflowVersion, allowing testing across engine versions without changing workflow source. The feature is available in all AWS HealthOmics regions and supports HIPAA-eligible, production-regulated workflows.

🔔 Amazon Connect Customer now automates placement of ad-hoc activities in agent schedules to minimize impact on service level goals. When scheduling events like training or meetings, supervisors can select placement within a shift, inside a specific time window, or relative to shift boundaries, and the system finds the optimal time within those constraints. This reduces manual scheduling effort and preserves consistent service levels across teams.

🔔 Amazon Connect Customer now supports scheduling up to 5,000 agents per schedule, simplifying workforce planning for large or multi-skilled agent pools. Additional limits include up to 350 agents per staffing group and 300 staffing groups per forecast group, enabling a forecast group capacity of up to 5,000 agents. The update removes the need to split schedules or maintain separate schedules for shared agent pools, reducing operational complexity and improving schedule optimization. This feature is available in all AWS Regions where Amazon Connect Customer agent scheduling is offered.